Tag: Doug Griffin

We live in an age of simplistic explanations. We build simple systemic models and crude abstractions. As a result, both our sense making and our decisions are built on an inadequate appreciation of the complex systems we are part of.

We have seen what it can lead to: industrial farming has caused a radical reduction of variety in nature in order to meet the goals of productivity. The simplification of crops was economically very efficient, allowing specialization in machinery and lowering the cost of learning, but it often damaged the local ecology in an irreversible way. The result was a fragile ecosystem, with a growing dependency on artificial fertilizers.

Every time we replace natural, complex systems with simplified mono-cultures we gain in short-term productivity, but at the cost of long-term resilience and viability.The less diverse a system is, the more vulnerable it is, and the more unsustainable it becomes.

Farming is now changing. New voices within agriculture say that “all farming takes place in a unique space and time”. These scholars claim that a mechanical application of generic rules and principles that ignore these contextual particularities is an invitation to catastrophic failure.

The principles of simplification still apply to the social systems of work: most of our firms can be described as mono-cultures. We also do our best to productize humans to fit the job markets.Many organizations are productive in the short term, but fragile in the long term. As long as the environment remains the same, simplified systems are very efficient, but they immediately become counterproductive when the environment changes even slightly. And it always will.

Our view of efficiency in firms still follows the line of thinking of efficiency on farms.

Job markets need standardized workers who are uniform in their skills and motivations. People are interchangeable labor. These people have no uniqueness. They have no original ideas to contribute to work. The focus is on the price of work; supply and demand.

In classical economic theory, markets are assumed to tend to a state of equilibrium. If there is an increase in demand, prices rise to encourage a reduction in demand and/or an increase in supply to match the demand. This is the principle behind Uber’s surge pricing. A market, then, is a simple cybernetic system: any significant change is self-regulating adaptation. There is no learning.

One-dimensional social designs have the same inbuilt risks as simplified natural designs. Simplified social systems can cause the same kind of damage to the human ecology as simplified farming systems have caused to the natural ecology. People become dependent on artificial motivation systems, the human equivalents of fertilizers. We call them incentives.

Just as all sustainable farming is now seen as taking place in a unique context, all human work takes place in a unique space and at a unique time. Human work is situated and context-dependent. It just hasn’t been understood that way. The digital architecture of this kind of work might resemble Amazon Dash buttons more than Uber.

Technological intelligence helps farmers to be more context-aware. Technological intelligence can do the same for human work. Mass systems were built on general knowledge and generic competences. Perhaps post-mass systems are going to be built more on situated knowledge and contextual competences.

An example of this might be the difference between the general knowledge of seamanship in open waters and the contextual knowledge of piloting. When a ship approaches land, the captain often hands over control to a local pilot, who then navigates the ship to the port. Pilots know well the dynamic peculiarities of the area, the winds and the currents. Much of this situated knowledge would be irrelevant somewhere else, at another harbor entrance.

A job market, as a concept, is a radical abstraction of human work. Every time we replace practical, local knowledge with general, standardized knowledge we gain in productivity, but at the cost of more environmental adaptation in the future. Learning debt is created and the whole system (of jobs) is less resilient and may even become dysfunctional. Short-term gains turn out to be extremely expensive in the long run!

The post-industrial era is too complicated to boil down into a single slogan describing work, but three scenarios seem to be emerging: (1) processes are automatized and robotized, leading to an algorithmic economy: (2) generic work is found through platforms, or turned into tasks circling the world, leading to a platform economy, and (3) context-specific value creation takes place in interaction between interdependent people, leading to an entrepreneurial economy.

I believe that the future of human work is contextual. Even after the captains are automated, the pilots may still be human beings. Even after the surgeons are robots, the nurses may still be human beings. Some people doubt this because there is some very advanced research going on that explores sensor technologies and responsive algorithms. The collaboration between sensors and actuators is getting better and better. Despite that, if you are a human being, it is better to be a tour guide than a travel agent.

It is a more profound change in work patterns than what the present platforms offer. It is not about employees becoming contractors. It is about generic, mass solutions becoming contextual and about interchangeable people who are now, perhaps for the first time, being seen as unique. The case for networked small units, such as human beings working together in responsive interaction, is stronger than ever. Local, contextual knowledge is needed not only for sustainability in farming but also at work.

What is most desperately needed is a deeper understanding of the complexity of life.

Farming is starting more and more with a true understanding of the particularities of the land. Work should also start with an understanding of the particularities of human beings.

The concepts that govern our thinking and language in relation to work are not just semantic entities, but influence what we perceive and what we think is possible or not possible. Usually we are not aware of how these concepts prime our thinking. We simply think and act along certain lines.

A seminal concept related to how we perceive work is the division of labor, the notion of work as activities separated from other activities, as jobs. The industrial management paradigm is based on the presupposition that activities are the independent governing factors of creating value. The organizational structure of jobs comes first. Then an appropriate system of co-ordination and communication is put into effect. The scheme of interaction conforms to the planned division of labor as a secondary feature.

What if the increasing global competition, the Internet and the huge advances in communication technologies made it possible, or even necessary, to think differently? What if interaction was seen as the governing factor? The smartphone has now become information technology’s key product. Surely, then, it has an impact on the way we work. As jobs and communication are mutually dependent, it means that if there are changes in interaction, so the activities will change.

In the mainstream conceptual model of communication (Shannon & Weaver 1948) a thought arising within one individual is translated into words, which are then transmitted to another individual. At the receiving end, the words translate back into the same thought, if the formulation of the words and the transmission of those words are good enough. The meaning is in the words.

Amazingly, our conceptualization of value creation has followed the very same model. Companies transform ideas into offerings that are delivered to customers. At the receiving end, the products translate back into the same value that the company has created. The meaning is in the product.

Management scholars have lately made interesting claims saying that although the product is the same, different customers experience the value potential of the product differently. They say that it is in fact wrong to say that companies create value. It is the way the offering is contextually experienced and used that creates value, more value or less value. The bad news is that our present conceptualizations of work make it very hard to do anything about it. The good news is that for the first time in history we can do something about it. Companies can connect with users and be digitally present when and where their products are used.

But we need a new conceptualization of communication if we want to have a new conceptualization of work. Luckily, there is one. A completely different approach to communication exists. The alternative view is based on the work of George Herbert Mead. This model does not see communication as messages that are transmitted between senders and receivers, but as complex social action.

In the social act model, communication takes the form of a gesture made by an individual that evokes a response from someone else. The meaning of the gesture can only be known from the response, not from the words. There is no deterministic causality, no transmission, from the gesture to the response. If I smile at you and you respond with a smile, the meaning of the gesture is friendly, but if you respond with a cold stare, the meaning of the gesture is contempt. Gestures and responses cannot be separated but constitute one social act, from which meaning emerges.

Gestures call forth responses and products call forth and evoke responses. Value lies not in the product but in the (customer) response. Accordingly, work should then be conceptualized as an interactive process, a social act, because the value of work cannot be known in the separate “job” activity or be understood through the capabilities of the worker.

If we subscribe to this relational view, it means that people and actions are simultaneously forming and being formed by each other at the same time, all the time, in interaction. Perhaps in the future it will not be meaningful to conceptualize work as jobs or even as organizational (activity) structures like the firms of today. Work will be described as complex patterns of communicative interaction between interdependent individuals.

All interacting imposes constraints on those relating, while at the same time enabling those people to do what they could not otherwise do. Enabling and energizing patterns of interaction may be the most important raison d’être of work.

The relational view is a new conceptualization of work, potentially opening up new opportunities to disrupt unemployment. Perhaps it is time to change the focus from creating jobs to creating customers – in new, innovative ways. To quote Max Planck: “If you change the way you look at things, the things that you look at change.”

The way we want to make sense of the world around us often has to do with causality. The question we ask is what caused “it” to happen. The mainstream approach is that an arrow, or arrows, can be drawn. There is a variable, the “it”, that happened, that is now to be explained. In scientific study this variable is regarded as dependent. An independent variable, or variables, that cause it are then sought. Causality means that X causes Y. If there is more X there will also be more Y. This is the if-then model of management. In organizations, a familiar explanation for success is that a particular manager or a particular culture caused it.

But there is something significant happening today. Scholars are increasingly pointing out the fact that this view of the relationship between cause and effect is much too simplistic and leads to a very limited or even faulty understanding of what is really going on.

Cybernetics recognized a much more complicated causality. In this kind of system the arrows, the links, between cause and effect can be distant in terms of time or place. The system can be highly sensitive to some changes but very insensitive to some others. For the first time, it was understood that it is a non-linear world.

Complexity challenges the assumption of earlier systems theories that movement in time can be predictable in the sense that X causes Y, or that the movement follows some archetypes. The modelling differs significantly from all previous systems models.

Complexity means a different theory of causality.

The most important insight is that it is often not possible to identify specific causes that yield specific outcomes. Almost indefinite number of variables influence what is going on. The links between cause and effect are lost because the tiniest overlooked, or unknown, variable can escalate into a major force. And afterwards you can’t trace back, you can’t find the exact butterfly that flapped its wings. There is no trail that leads you to an independent variable.

The future of a complex system is emerging through perpetual creation. Complexity is a movement in time that is both knowable and unknowable. Uncertainty is a basic feature of all complex systems. It is a dynamic in time that is called paradoxically stable instability or unstable stability. Although the specific paths are unpredictable, there is a pattern. The pattern is never exactly the same, but there is always some similarity to what has happened earlier.

In the end it is about the combination and interaction of the elements that are present and how absolutely all of them participate in co-creating what is happening. None of the elements cause the end result independently. From this standpoint a lighted match does not cause a fire. Rather, the fire took place because of a particular combination of elements of which the lighted match was just one. In the same way, a rude remark does not start a fight. The argument starts as a combination of an offensive remark and a coarse response.

The big new idea is to reconfigure agency in a way that brings complex relationships into the center. The task today is to see action within these relationships.

Complex relationships cannot be understood through spatial metaphors such as process maps or network charts. Unhelpful or wrong models and metaphors are often a big obstacle to moving our thinking forward after the technological constraints are gone.

We need to move towards temporality, to understand what is happening in time.

An organization is not a whole consisting of parts. There is no inside and outside. An organization is a continuously developing or stagnating pattern in time. Industrial management was a particular pattern based on specific assumptions about communication, causality and human psychology.

Recent developments in psychology/sociology have shown that human agency is not located or stored in an individual, contrary to what mainstream economics would have us believe. The individual mind arises continuously in communication between people.

The focus of industrial management was on the division of labor and the design of vertical/horizontal communication channels. The focus should now be on cooperation and emergent interaction based on transparency, interdependence and responsiveness.

Looking at communication, not through it, what we are creating together.

The characteristics of work in the network economy are different from what we are used to: the industrial production of physical goods was financial capital-intensive, leading to centralized management and manufacturing facilities where you needed to be at during predetermined hours. The industrial era also created the shareholder capitalism we now experience. In the network economy, individuals, interacting with each other by utilizing free or low cost social platforms and relatively cheap mobile, smart devices, can now create information products.

The production of information goods requires more human capital than financial capital. And the good news is that you are not limited to the local supply. Because of the Internet, work on information products does not need to be co-located. The infrastructure of work does not resemble a factory but a network.

Decentralized action plays a much more important role today than ever before.

Work systems differ in the degree to which their components are loosely or tightly coupled. Coupling is a measure of the degree to which communication between the components is predetermined and fixed or not. The architecture of the Internet is based on loose couplings and modularity. Modularity is the design principle that intentionally makes nodes of the network able to be highly responsive.

The Internet-based firm sees work and cognitive capability as networked communication. Any node in the network should be able to communicate with any other node on the basis of contextual interdependence and creative participative engagement. Work takes place in a transparent digital environment.

As organizations want to be more creative and knowledge-based, the focus of management thinking should shift towards understanding participative, self-organizing responsiveness.

The Internet is a viable model for making sense of the new value creating constellations of tomorrow.

But something crucially important needs to change:

The taken for granted assumption is that it is the independent employer/manager who exercises freedom of choice in choosing what is done and by whom. The employees of the organization are not seen autonomous, with a choice of their own, but are seen as rule-following, dependent entities. People are resources.

Dependence is the opposite of taking responsibility. It is getting the daily tasks that are given to you done, or at least out of the way. We are as used to the employer choosing the work objectives as we are used to the teacher choosing the learning objectives. The manager directs the way in which the employee engages with work, and manages the timing and duration of the work. This image of work is easy to grasp because it has been taught at school where the model is the same.

In contrast to the above, digital work and the Internet have brought about circumstances in which the employee in effect chooses the purpose of work, voluntarily selects the tasks, determines the modes and timing of engagement, and designs the outcomes. The worker here might be said to be largely independent of some other person’s management, but is in effect interdependent. Interdependence here means that the worker is free to choose what tasks to take up, and when to take them up, but is not independent in the sense that she would not need to make the choice.

The interdependent, task-based worker negotiates her work based on her own purposes, not the goals of somebody else, and chooses her fellow workers based on her network, not a given organization. The aim is to do meaningful things with meaningful people in meaningful ways utilizing networks and voluntary participation.

It is not the corporation that is in the center, but the intentions and choices of individuals. This view of work focuses attention on the way ordinary, everyday work-tasks enrich life and perpetually create the future we truly want through continuous learning.

The architecture of work is not the structure of a corporation, but the structure of the network. The organization is not a given hierarchy, but an ongoing process of organizing. The main motivation of work is not financial self-interest, but people’s different and yet, complementary expectations of the future.

The factory logic of mass production forced people to come to where the work is. The crowdsourcing logic of mass communication makes it possible to distribute work/tasks to where the right/willing/inspired people are, no matter where on the globe they may be.

Knowledge work is not about jobs or job roles but about tasks. Most importantly knowledge work can, if we want, be human-centric. Through mobile smart devices and ubiquitous connectivity, we can also create new opportunities and a better future for millions of presently unemployed people.

The approach of the industrial era to getting something done is first to create an organization. If something new and different needs to be done, a new and different kind of organizational form needs to be put into effect. Changing the lines of accountability and reporting is the epitome of change in firms. When a new manager enters the picture, the organizational outline is typically changed into a “new” organization. But does changing the organization really change what is done? Does the change actually change anything?

An organization is metaphorically still a picture of walls defining who is inside and who is outside a particular box. Who is included and who is excluded. Who “we” are and who “they” are.

This way of thinking was acceptable in repetitive work where it was relatively easy to define what needed to be done and by whom as a definition of the quantity of labor and quality of capabilities.

As a result, organizational design created two things: the process chart and reporting lines, the hierarchy.

In creative, knowledge based work it is increasingly difficult to know the best mix of people, capabilities and tasks in advance. In many firms reporting routines are the least important part of communication. Much more flexibility than the process maps allow is needed. Interdependence between peers involves, almost by default, crossing boundaries. The walls seem to be in the wrong position or in the way, making work harder to do. What, then, is the use of the organizational theatre when it is literally impossible to define the organization before we actually do something?

What if the organization really should be an ongoing process of emergent self-organizing? Instead of thinking about the organization, let’s think about organizing.

If we take this view we don’t think about walls but we think about what we do and how groups are formed around what is actually going on or what should be going on. The new management task is to make possible the very easy and very fast emergent formation of groups and to make it as easy as possible for the best contributions from the whole network to find the applicable tasks, without knowing beforehand who knows.

The focal point in organizing is not the organizational entity one belongs to, or the manager one reports to, but the reason that brings people together. What purposes, activities and tasks unite us? What is the cause of interdependence and group formation?

It is a picture of an organization without walls, rather like contextual magnetic fields defined by gradually fading rings of attraction.

Instead of the topology of organizational boxes that are still often the visual representation of work, the architecture of work is a live social graph of networked interdependence and accountability. One of the most promising features of social technologies is the easy and efficient group formation that makes this kind of organizing possible for the first time!

It is just our thinking that is in the way of bringing down the walls.

Gregory Bateson wrote that the major problems in the world are the result of the difference between how nature works and how people think. Mainstream economics still sees the economy and society as ultimately predictable and controllable (machines), although the repeated financial crises have shown how deeply flawed this view of the world is.

Luckily, during 2013, more scholars than ever before saw organizations as being more analogous to nature. There, it is not about predictions and control, but about perpetual co-creation, complex responsive processes and fundamental interdependence. Their claim is that we should study links and interactions. Many aspects of our social and economic world would start to look completely different from this complex network perspective.

2013 also brought us closer to understanding how work itself is changing.

Knowledge work is creative work we do in interaction. Unlike the business processes we know so well, where tangible inputs are acted on in some predictable, structured way and converted into outputs, the inputs and outputs of knowledge work are ideas, information and decisions. Even more, there are no predetermined task sequences that, if executed, would guarantee success. Knowledge work is characterized by variety and exception rather than routine. It is thus impossible to separate a knowledge process from its outcomes. Knowledge work is not “just work”, a means to doing something else! Knowledge work is about human beings being more intensely present. Thus, a business today needs to be human-centric – by definition.

The good news then, is the advances during 2013 in network theory and knowledge work practices. The bad news, as we now look ahead to 2014, is that today we are as far from being human-centric, as we have been for ages. As one example, people still tend to see their work and personal lives as two separate spheres. Although this conflict is widely recognized, it is seen as an individual challenge, a private responsibility to manage.

It is now time to challenge this and see the conflict as a systemic problem. It is a result of the factory logic, which saw human beings as controllable resources and interchangeable parts of the main thing, the production machinery. The context and logic of work are dramatically different today. In knowledge work we need to create an explicit, new connection between work and personal life. We talked earlier about balancing work and life. Here we are talking about connecting work and life in a new way, with a new agenda. Human beings are the main thing.

Traditional management thinking sets employee goals and business goals against each other. The manager is free to choose the goals, but the employee is only free to follow or not to follow the given goals. This is why employee advocates mainly want socially responsible firms, nothing else, and the management of those firms wants committed employees who come to work with enthusiasm and energy. Must we then choose between the goals of the people or the goals of the business, or can the two sides be connected? As we know, passion and commitment are best mobilized in response to personal aspirations, not financial rewards. We need a new agenda connecting people and businesses! The aim, however, is not to have a single set of common goals, but complementary goals and a co-created narrative for both!

Linking personal lives with corporate issues may seem like an unexpected, or even unnecessary connection. But if we don’t learn from network theory and knowledge work practices, and continue to deal with each area separately, both individuals and organizations will suffer. The lack of a connecting agenda may also be one of the big challenges facing the emerging post-industrial society.

We need to study the intersection of business strategy and personal narrative and use the new agenda to challenge our industrial age practices and flawed ways of thinking. Knowledge work needs whole human beings. People who are more fully present, people with responsibility and ownership. We are accustomed to taking work home, but what would the opposite be? This may be the next frontier of social business. More on this next year!

Christmas is a special time for family and friends. Perhaps the rest of the year can also be made very special through rethinking and reinventing some of the basic beliefs we have about work!

We have been studying companies’ connections and disconnections for more than twenty years and have worked inside a huge number of them. Across all this research, common themes have emerged and intensified during the past few years: good communication in the era of the Internet and the new interactive tools does not mean any more that companies should listen carefully to their customers or that leaders should talk clearly with their subordinates. The linear view of communication, the movement of messages or sharing of content between people is giving way to a totally new understanding of what interaction, and work, are all about.

The first emerging theme is that communication is in fact a process of continuous coordination and knowledge creation. Knowledge is not shared as contents, but arises in action. Knowledge is never transmitted from one mind to another. It is a change from the movement of messages to a joint movement of thought. The future and viability of an organization depend on this process.

Economics still makes the assumption that individuals, the agents, as they are called, operate autonomously, separately from the influences of others. When choosing something, making a decision from a set of alternatives, the agent compares the attributes of the alternatives and selects the one that corresponds to her preferences. It is a world where independent individuals carefully weigh up the costs and benefits of any particular course of action.

However, scientists have emphasized the limits of our understanding. An important point is that these limits apply to everyone. They apply to politicians, to central bankers and to top executives of multinational companies. John Maynard Keynes once wrote that we have, as a rule, only the vaguest idea of the consequences of our actions. Herbert Simon and Stuart Kauffman on the other hand have argued that the number of future paths open to us at any point in time is so vast that it makes no sense at all to speak of the best or optimal decision. But we still think the world works like a predictable machine operated by rational agents

Behavior that does not follow an economist’s definition is often called irrational, but it may be that in a world of ubiquitous networks, a proliferation of choice and an abundance of information, the economic definition of rationality has itself become outdated and irrational.

We need a new model of rational behavior and a new understanding of how we make decisions. We need a new decision model!

The second emerging theme is that the assumption that people make choices in isolation, that they do not adopt opinions simply because other people have them, is no longer sustainable. The choices people make, their buying decisions and their political views, are directly influenced by other people. That is to say that we construct our world together in communication. Network scientists such as Duncan Watts and Mark Granowetter have proved that the world comes to be what it is for us in our relationships. In the end it all depends on the company you keep and the conversations you have.

This leads to the importance of emphasizing relations instead of reductionism and separations. Reductionism means that the organization is understood as being split from its environment and one functional team is seen as being separate from another function. The worst mistake we make as a result of reductionist thinking may be that we assess and reward employees as if they were disconnected from other employees.

Links and communication are at the centre of organizational life. Depending on the quantity of interdependent links and the quality of communication, the organization lives or dies. Work is interaction between interdependent people.

The third emerging theme is that communication creates patterns. Words become what they are through the responsive actions of the people taking part. The relational view means in practice that if a conversation goes badly, it is always a joint achievement. On the other side, a conversation can only be successful if both participants join in and make it so as Ken Gergen points out. In management, it means that there is nothing one person alone can do to be a good manager. Good ideas don’t count as good ideas, if other people don’t treat them as such.

New leadership is about an awareness of creative and destructive patterns and having the ability to influence what is going on. In a creative pattern, the participants build on each other’s contributions. The conversation, thinking and action are in a process of forward movement.

Destructive patterns are the most harmful in terms of organizational viability. These patterns don’t contain forward movement but running in circles. People and organizations get stuck! People slow down in bitterness and silence, or even to the breaking of the link. The most destructive patterns often begin subtly, but unless they are worked with soon, not only will relations suffer but the whole network will deteriorate.

Being aware of the patterns includes being aware of the roles that we play. Whenever we speak, we do two things: we subtly define ourselves and define the other. Does the speaker in a company context define herself as one who can talk down to others or as an equal? What we say is important to the viability of the organization but the way we say it can be equally important. Talking down or talking up between people creates an asymmetry that leads to bad decisions and inefficient movement of thought.

The machine metaphor meant that we tended to think that the people “above” us have significant power. They are in control. We thus talked up to them. They should decide. They should do things for us because they were the ones who were responsible, not us. Knowing that they are not in control raises the question of a need for a new distribution of responsibility. Bottom-up as a metaphor is as harmful as top-down when the common goal is resilience.

There is no aspect of work or leadership that takes place outside the realm of communication. Human agency is not located or stored in an individual, contrary to mainstream economics. The individual mind arises continuously in communication between people.

Being skilfully present in the forward movement of thought and relational action is the new meaning of being rational.

Up to now, we have seen the world around us as systems that, we thought, could be described and understood by identifying rational causal links between things: if I choose X, then it will lead to Y. If, on the other hand, I choose A, it will lead to B. We are accustomed to drawing boxes and arrows between those boxes. We try to model the world as predictable processes based on knowing how things are and how they will be. We want to be certain, and we think we are.

Management thinking is based on the sciences of certainty. The whole system of strategic choice, goal setting and choosing actions to reach the given goals in a controlled way depends on predictability. The problem is that this familiar causal foundation cannot explain the reality we face. Almost daily, we experience the inability of leaders to choose what happens to them, to their organizations – or to their countries. Things may appear orderly over time, but are inherently unpredictable. We live in a complex world.

Complex systems are, as their name implies, hard to understand. Social systems, like organizations consisting of people, are accordingly complex and hard to understand. There is no linearity in the world of human beings. There are no arrows and people are not boxes, or fit inside of boxes. This is why our thinking needs to develop from the sciences of certainty to something more applicable, the sciences of uncertainty, the sciences of complexity.

Complexity refers to a pattern, a movement in time that is, at the same time, predictable and unpredictable, knowable and unknowable. Chaos theory explains how these patterns form. A parameter might be the flow of information in the system. At low rates, meaning no input or more of the same input, the system moves forward displaying a repetitive, stuck behavior. At higher rates and more diversity the pattern changes. At very high rates the system displays a totally random behavior. The pattern is highly unstable. However, there is a level between repetition/stability and randomness/instability. This level where simultaneous coherence and novelty are experienced is called the edge of chaos.

Classical physics took individual entities and their separate movement (trajectories) as the unit of analysis in the same way we have analyzed and rewarded individuals. Henri Poincaré was the first scientist to find that there are two distinct kinds of energy. The first was the kinetic energy in the movement of the particle itself. The second was the energy arising from the interaction between particles. When this second energy is not there, the system is in a state of non-dynamism. When there is interactive energy, the system is dynamic and capable of novelty and renewal.

Interaction creates resonance between the particles. Resonance is the result of coupling the frequencies of particles leading to an increase in the amplitude. Resonance makes it impossible to identify individual movement in interactive environments because the individual’s trajectory depends more on the resonance with others than on the kinetic energy contained by the individual itself.

We are the result of our interaction. We are our relations.

The conclusions are important for us: firstly, novelty always emerges in a radically unpredictable way. The smallest overlooked variable or the tiniest change can escalate by non-linear iterations into a major transformative change in the later life of the system.

Secondly, the patterns are not caused by competitive selection or independent choices made by independent agents. Instead, what is happening happens in interaction, not by chance or by choice, but as a result of the interaction itself.

The new social technologies have the potential to influence connectivity and interaction as much as the sciences of complexity are going to influence our thinking. The task today is to understand what both social business and complexity mean. The next management paradigm is going to be based on those two, at the same time.

Economic growth is about value added. In manufacturing adding value was a transformation process from physical raw materials to physical goods. Economic growth is still today about value added. The difference is that the generic, homogeneous raw materials of the industrial era are now unique ideas and the transformation process is an iterative, interactive, non-linear movement, rather than a linear, sequential chain of acts.

The worlds of manufacturing-based added value and creativity-based added value require very different skills. Before the Internet and smart devices, most professional occupations required individual competencies that in most cases had accumulated over years. This experience base, often called tacit knowledge, was used to retrieve answers from memory and to independently solve situations arising at work. Knowledge was situated in the individual. In order to help individuals cope with the challenges of everyday life, individual competencies needed to be developed. This is why our whole education system is still based on independent individuals learning and, as a consequence, knowing.

The cognitive load of work has increased as a result of manufacturing giving way to creative, knowledge-intensive work. The content of work is changing from repetitive practices to contextual, creative practices. This makes the individual experience base, by default, too narrow a starting point for efficient work. Experiences can be a huge asset but experiences can also be a liability, creating recurrence where there should be novelty and innovation.

Creative work is not performed by independent individuals but by interdependent people in interaction. A new way to understanding work and competencies is unfolding: knowledge that used to be understood as the internal property of an individual is seen as networked communication. This requires us to learn new ways of talking about education and competencies. What is also needed is to unlearn the reductionist organizing principles of industrial work. Work is communication and the network is the amplifier of creativity.

People have always networked. Scholars depended largely on correspondence networks for the exchange of ideas before the time of the universities. These communities, known as the “Republic of Letters” were the social media of the era, following the communication patterns of today astonishingly closely. The better-networked scientist was often the better scientist. The better-networked worker is today usually the better worker. The better-networked student in the future is always the better student.

The main difference from the time of the Republic of Letters is the efficiency of our tools for communication, meaning thinking together. A “man of letters” may today be a man of tweets, blog posts and Facebook, but the principle is the same: the size and quality of the network matters. What matters even more than the network, is networking, the way we are present and interact. It is time to acknowledge the inherently creative commons nature of thinking, creativity and economic growth.

Life is a temporal pattern of emotional and intellectual interaction. We are our interaction.

Many people say that open source software developers have the most efficient ecosystems for learning that have ever existed. What is it, then, that is so special about the way developers do things? Is there something that could act as a model for the future of work, or the future of education?

What takes place in open source projects is typically not the result of choices made by a few (powerful) people that others blindly implement. Instead, what emerges is the consequence of the choices of all involved in the whole interconnected network, “the connective“, as Stowe Boyd puts it. What happens does not follow exactly a plan or a design, what happens emerges. It is about the hard to understand process of self-organization.

We still don’t quite understand what emergence and self-organization mean. The problem is that we believe that the unit of work is the independent individual. Self-organization is then thought to mean that individuals organize themselves without the direction of others. People think that it is a form of empowerment, or a do-whatever-you-like environment, in which anybody can choose freely what to do. But connected people can never simply do what they like. Cooperating individuals are not, and cannot be, independent. People are interdependent. Interdependence means that individuals constrain and enable each other all the time. What happens, happens always in interaction and as a result of interaction.

According to the present approach to management, planning and enactment of the plans are two separate domains that follow a linear causality from plans to actions. From the perspective of open source development, organizational outcomes explicitly emerge in a way that is never just determined by a few people, but arises in the ongoing local interaction of all the people taking part. For example GitHub “encourages individuals to fix things and own those fixes just as much as they own the projects they start”.

What emerges is, paradoxically, predictable and unpredictable, knowable and unknowable at the same time. This does not mean dismissing planning, or management, as pointless, but means that the future always contains surprises that the managers cannot control. The future cannot be predicted just by looking at the plans.

Emergence is often understood as things which just happen and there is nothing we can do about it. But emergence means the exact opposite. The patterns that emerge do so precisely because of what everybody is doing, and not doing. It is what many, many local interactions produce. This is what self-organization means. Each of us is forming plans and making decisions about our next steps all the time. “What each of us does affects others and what they do affects each of us.”

No one can step outside this interaction to design interaction for others.

An organization is not a whole consisting of parts, but an emergent pattern in time that is formed in those local interactions. It is a movement that cannot be understood just by looking at the parts. The time of reductionism as a sense-making mechanism is over.

What we can learn from the open source ecosystems is that organizational sustainability requires the same kind of learning that these software developers already practice: “All work and learning is open and public, leaving tracks that others can follow. Doing and learning mean the same thing.”

The biggest change in thinking that is now needed is that the unit of work and learning is not the independent individual, but interdependent people in interaction.